Meaning
Efficient numerical methods allow processors to solve high order equations using the minimal number of multiplications and additions. Within embedded systems, Horner Polynomial Evaluation organizes the calculation into a nested sequence that avoids the exponentiation operator. This approach reduces the cumulative error that builds up in low precision hardware.
It works best for transforming raw sensor voltages into usable physical units like pressure or temperature.
Compute Cycle
Savings in CPU cycles allow longer sleep periods for battery powered devices. Using Horner Polynomial Evaluation ensures that complex calibration curves do not drain the power supply of a field monitor. Developers swap standard math libraries for these optimized routines during compile time.
Precision Loss
Floating point errors are minimized by the specific order of arithmetic operations used in the method. Because Horner Polynomial Evaluation handles coefficients in a recursive fashion, the small rounding errors do not multiply as quickly as they do in direct power series expansion. Accuracy remains high across the entire operational range.
Algorithm Structure
Code blocks are written to handle arrays of values representing the polynomial degree. The logic inside Horner Polynomial Evaluation starts at the highest coefficient and multiplies downward. Results emerge in microsecond timeframes.
